Changeset 978


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Timestamp:
Mar 23, 2011, 2:58:41 PM (8 years ago)
Author:
lindanl
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some changes to 04

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docs/PACT2011
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  • docs/PACT2011/04-methodology.tex

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    4 In this section, we describe our methodology for the measurements and investigation of XML parsing energy consumption and performance. In brief, for each of the XML parsers under study we propose to measure and evaluate the energy consumption required to carry out XML well-formedness checking, under a variety of workloads, and as executed on both mobile device and server hardware.
     4In this section, we describe our methodology for the measurements and investigation of XML parsing energy consumption and performance.
     5In brief, for each of the XML parsers under study we propose to measure and evaluate the energy consumption required to carry out XML well-formedness checking,
     6under a variety of workloads, and as executed on three different Intel cores.
    57
    6 To begin our study, we propose to first investigate each of the XML parsers in terms of the PMCs hardware events as listed in the following subsection. Based on previous key works \cite{bellosa2001, bertran2010, bircher2007}, we have chosen several key hardware performance events for which the authors indicate have a strong correlation to energy consumption. From these data, we hope to gain insight into the XML parser execution characteristics which most significantly contribute to overall energy consumption. Secondly, using the Fluke i410 current clamp meter, we plan to measure the total energy consumption required to complete XML well-formedness checking for each XML parser, on each hardware platform, and for each of a number of XML source files.
     8To begin our study, we propose to first investigate each of the XML parsers in terms of the PMCs hardware events as listed in the following subsection.
     9Based on previous key works \cite{bellosa2001, bertran2010, bircher2007},
     10we have chosen several key hardware performance events for which the authors indicate have a strong correlation to energy consumption.
     11From these data, we hope to gain insight into the XML parser execution characteristics which most significantly contribute to overall energy consumption.
     12Secondly, using the Fluke i410 current clamp meter, we plan to measure the total energy consumption required to complete XML well-formedness checking for each XML parser,
     13on each hardware platform, and for each of a number of XML source files.
    714
    815The foundational work by Bellosa in \cite{bellosa2001} as well as more recent work in \cite {bircher2007, bertran2010}
     
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    18 % The use of performance counters for modeling power is not a new concept.
    19 
    20 %Although the microprocessor is typically the largest consumers of power, Bertran et al. found that the chipset, memory, I/O, and disk may can account for a significant of the total system energy consumption \cite{bertran2010}.
    21 
    22 %As such, through the selection of a representative subset of hardware performance events, as based on the combined works of  \cite{bellosa2001, bertran2010, bircher2007}, we hope to gain insight into the XML parser execution characteristics which contribute most significantly to overall energy consumption.
    23 
    24 The following subsections describe the XML parsers under study, XML workloads, the mobile device and server hardware architectures, PMC hardware events selected for measurement, and the Fluke i401 current clamp meter. The expected outcomes of this section are hardware performance counter measurements and total energy consumption measurements for each of XML parser, XML source file, and hardware combination.
     24The following subsections describe the XML parsers under study, XML workloads, the hardware architectures, PMC hardware events selected for measurement, and the Fluke i401 current clamp meter.
     25The expected outcomes of this section are hardware performance counter measurements and total energy consumption measurements for each of XML parser, XML source file, and hardware combination.
    2526
    2627\subsection{Parsers}\label{parsers}
    2728
    2829The XML parsing technologies selected for this study are the Parabix2, Xerces-C++, and Expat XML parsers.
    29 Parabix2 \cite{parabix2} (parallel bit streams for XML) is the second generation Parabix parser. Parabix2 is an open-source XML parser that leverages the SIMD capabilities of modern commodity processors; it employs the new parallelization techniques using parallel parsing with bit stream addition to deliver dramatic performance improvements over traditional byte-at-a-time parsing technology.
     30Parabix2 \cite{parabix2} (parallel bit streams for XML) is the second generation Parabix parser. Parabix2 is an open-source XML parser that leverages the SIMD capabilities of modern commodity processors;
     31it employs the new parallelization techniques using parallel parsing with bit stream addition to deliver dramatic performance improvements over traditional byte-at-a-time parsing technology.
    3032Xerces-C++ version 3.1.1 (SAX) \cite{xerces} is a validating open source XML parser written in C++ by the Apache project.
    3133Expat version 2.0.1 \cite{expat} is a non-validating XML parser library written in C.
     
    4951
    5052Distinguishing between "document-oriented" XML and "data-oriented" XML is a popular way to describe the two basic classes of XML documents.
    51 Data-oriented XML is used as an interchange format. Document-oriented XML is used to impose structure on information that rarely fits neatly into a relational database--particularly information intended for publishing. Data-oriented XML are characterized by a higher markup density. Markup density is defined as the ratio of the total markup contained within an XML file to the total XML document size.  This metric may have substantial influence on the performance of XML parsing. As such we choose workloads with distinguishable markup densities.
     53Data-oriented XML is used as an interchange format.
     54Document-oriented XML is used to impose structure on information that rarely fits neatly into a relational database--particularly information intended for publishing.
     55Data-oriented XML are characterized by a higher markup density.
     56Markup density is defined as the ratio of the total markup contained within an XML file to the total XML document size.
     57This metric may have substantial influence on the performance of XML parsing.
     58As such we choose workloads with distinguishable markup densities.
    5259
    53 Table \ref{XMLDocChars} shows the document characteristics of the XML instances selected for this performance study.
    54 The jawiki.xml and dewiki.xml XML files represent document-oriented XML instances of Wikimedia books,
    55 written in German and Japanese, respectively. The remaining files are data-oriented.
    56 The roads.gml file is an instance of Geography Markup Language (GML), a modeling language for geographic
    57 systems as well as an open interchange format for geographic transactions on the Internet.
    58 The po.xml file is an example of purchase order data, while the soap.xml file contains a large SOAP message.
    59 This markup density metric is reported for each
    60 document.\cite{CameronHerdyLin2008}
     60Table \ref{XMLDocChars} shows the document characteristics of the XML input files selected for this performance study.
     61The jawiki.xml and dewiki.xml XML files represent document-oriented XML inputs, containing three-byte and four-byte UTF8 sequence.
     62The remaining files are data-oriented inputs and consist of only ASCII characters.\cite{CameronHerdyLin2008}
    6163
    6264Describe parameters; what each parameter means.
     
    109111\hline
    110112Processor & Intel Core I5-2300 (2.80GHz) \\ \hline
    111 L1 Cache &  \\ \hline   
    112 L2 Cache &  \\ \hline
     113L1 Cache &  192 KB\\ \hline     
     114L2 Cache &  4 X 256KB \\ \hline
    113115L3 Cache & 6-MB \\ \hline
    114116Front Side Bus &  \\ \hline
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